Accurate Congenital Heart Disease Model Generation for 3D Printing

07/06/2019
by   Xiaowei Xu, et al.
1

3D printing has been widely adopted for clinical decision making and interventional planning of Congenital heart disease (CHD), while whole heart and great vessel segmentation is the most significant but time-consuming step in the model generation for 3D printing. While various automatic whole heart and great vessel segmentation frameworks have been developed in the literature, they are ineffective when applied to medical images in CHD, which have significant variations in heart structure and great vessel connections. To address the challenge, we leverage the power of deep learning in processing regular structures and that of graph algorithms in dealing with large variations and propose a framework that combines both for whole heart and great vessel segmentation in CHD. Particularly, we first use deep learning to segment the four chambers and myocardium followed by the blood pool, where variations are usually small. We then extract the connection information and apply graph matching to determine the categories of all the vessels. Experimental results using 683D CT images covering 14 types of CHD show that our method can increase Dice score by 11.9 and great vessel segmentation method in normal anatomy. The segmentation results are also printed out using 3D printers for validation.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
07/06/2019

Accurate Congenital Heart Disease ModelGeneration for 3D Printing

3D printing has been widely adopted for clinical decision making and int...
research
01/26/2021

ImageCHD: A 3D Computed Tomography Image Dataset for Classification of Congenital Heart Disease

Congenital heart disease (CHD) is the most common type of birth defect, ...
research
09/11/2018

Iterative Segmentation from Limited Training Data: Applications to Congenital Heart Disease

We propose a new iterative segmentation model which can be accurately le...
research
05/07/2020

Regression Forest-Based Atlas Localization and Direction Specific Atlas Generation for Pancreas Segmentation

This paper proposes a fully automated atlas-based pancreas segmentation ...
research
02/21/2019

Evaluation of Algorithms for Multi-Modality Whole Heart Segmentation: An Open-Access Grand Challenge

Knowledge of whole heart anatomy is a prerequisite for many clinical app...
research
07/23/2021

Cardiac CT segmentation based on distance regularized level set

Before analy z ing the CT image, it is very important to segment the hea...
research
07/24/2019

HeartFit: An Accurate Platform for Heart Murmur Diagnosis Utilizing Deep Learning

Cardiovascular disease (CD) is the number one leading cause of death wor...

Please sign up or login with your details

Forgot password? Click here to reset